Molecule Design

Latest papers

43 papers11 papers in the last four weeks, up 175% on the four weeks before. 0.1% of all new papers.

MolHop: Scaffold-Hopping Molecular Design with Agentic Reinforcement Learning
Oct 14, 2026Yanyi Su, Chenyan Wang, Yulei Gong +3Molecule Design Molecular Generation
State Key Laboratory of Physical Chemistry of Solid Surface, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, China · Shanghai Artificial Intelligence Laboratory, Shanghai, China · Institute of Artificial Intelligence, Xiamen University, Xiamen, China +1
MIPS: Mitigating Mode Collapse in Reinforcement Learning for Large Outcome Spaces
Oct 14, 2026Armaan Sandhu, Abhijeet Sinha, Dianbo LiuMolecule Design Reinforcement Learning
University of Massachusetts Amherst · National University of Singapore
LLM-to-Flow Distillation: Teaching Natural Language Goals to Scientific Generators
Oct 12, 2026Riccardo De Santi, Federico Di Gennaro, Angelo Gnazzo +6Molecule Design Large Language Model-Guided Scientific Discovery
ETH Zurich · ETH AI Center · Technische Universität Wien +3
MIRRA: Fast, High-Fidelity Molecular Generation with Chemistry-Informed Discrete Flow Matching
Oct 12, 2026Ge Sun, Juan J. de PabloMolecular Generation Molecular Graph Generation
Courant Institute of Mathematical Sciences, New York University, New York, NY 10012 · Tandon School of Engineering, New York University, Brooklyn, NY 11201 · Department of Physics, New York University, New York, NY 10003
AutoNovo: Agentic Program Search Discovers Transferable Nucleic Acid Design Algorithms
Oct 12, 2026Joel Shor, Subhashini VenugopalanMolecule Design Molecular Generation
AI Bio Design, Allen Institute & Move37 Labs · Google Research
FragFlex: Fragment-Based Flexible Molecular Generation for Exploring Vast Chemical Space
Oct 11, 2026Sihyun Park, David Ryan KoesMolecular Graph Generation Molecular Generation
Carnegie Mellon University · University of Pittsburgh
Information-Dense Synthesis for Molecular Discovery
Oct 6, 2026Kasper K. Jakobsen, Eli N. WeinsteinMolecular Optimization Drug Discovery
Department of Chemistry, Technical University of Denmark, Kgs. Lyngby, DK.
Navigating Route Latent Space for Synthesizable Molecular Design
Oct 6, 2026Tao Li, Tuan Vinh, Monika Raj +3Molecule Design Molecular Optimization
Department of Computer Science, Emory University · MRC Brain Network Dynamics Unit, University of Oxford · Department of Chemistry, Emory University +2
pCoMole: Pareto-Constrained Molecule Editing with Discrete Flows
Oct 1, 2026Tong Chen, Maximilian Holsman, Lin Zhao +1Constrained Generative Modeling Protein Design
Department of Computer and Information Science, University of Pennsylvania · Department of Computer Science, Duke University · Department of Bioengineering, University of Pennsylvania
One Sequence, Many Decodings: CAGenMol-2 Recasts Drug Design as Masked Molecular Inference
Sep 28, 2026Yanting Li, Enyan Dai, Lei Wang +2Molecular Optimization Masked Diffusion Models
The Hong Kong University of Science and Technology (Guangzhou) · Jinan University, Guangzhou
MolDesignBench: Evaluating LLM-based Agent for Scenario-grounded Molecular Design
Sep 23, 2026Yongjun Jeong, Hanbum Ko, Ye Rin Kim +6Molecular Optimization LLM Agent Evaluation
Department of Artificial Intelligence, Korea University · LG AI Research · Department of Statistics, Korea University
Ensemble-Conditioned Molecular Design
Sep 14, 2026Ross Irwin, Alessandro Tibo, Jon Paul Janet +1Molecular Optimization Structure-Based Drug Design
Molecular AI Discovery Sciences, R&D AstraZeneca Gothenburg, Sweden · Department of Computer Science and Engineering Chalmers University of Technology and University of Gothenburg Gothenburg, Sweden
Fraglingo: Molecular Design via Attachment-Aware Autoregressive Fragment Generation
Sep 11, 2026Thao Nguyen, Jeonghwan Kim, Zhenhailong Wang +1Molecular Generation Molecule Design
Siebel School of Computing and Data Science University of Illinois Urbana-Champaign Urbana, IL 61801, USA
NEAT-POCKET: Pocket-Conditioned Autoregressive 3D Molecular Generation with a Neighborhood-Guided Set Transformer
Sep 4, 2026Roxane Axel Jacob, Daniel Rose, Thierry Langer +13D Molecular Generation Molecular Generation
Department of Pharmaceutical Sciences, Faculty of Life Sciences, University of Vienna, Josef-Holaubek-Platz 2, 1090 Vienna, Austria. · Christian Doppler Laboratory for Molecular Informatics in the Biosciences, Department of Pharmaceutical Sciences, Faculty of Life Sciences, Josef-Holaubek-Platz 2, 1090 Vienna, Austria. · Vienna Doctoral School of Pharmaceutical, Nutritional and Sport Sciences (PhaNuSpo), Josef-Holaubek-Platz 2, 1090 Vienna, Austria.
Training Large Language Models for Small-Molecule Design with Synthetic Task Scaling
Sep 4, 2026Frank Hu, Shriram Chennakesavalu, Zichen Wang +5Molecule Design LLM Training
Prescient Design, Genentech, South San Francisco, CA, USA
PGFS++: Molecular Property Improvement under Synthesis and Diversity Constraints
Aug 19, 2026Boqiao Zhang, Godbless James, Sai Krishna Gottipati +1Molecular Optimization Molecule Design
University of Cambridge, United Kingdom · Graphcore, United Kingdom
Leveraging generative hallucination and biophysics-informed modeling for unified biomolecular sequence-structure co-design
Aug 18, 2026Xuefeng Liu, Mingxuan Cao, Xiao Luo +5Molecule Design Protein Design
Department of Medicine, University of Florida · Department of Computer Science, University of Chicago · Data Science Institute, University of Chicago +5
CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows
Aug 7, 2026Zhu Wang, Jiangyu Chen, Yingjun Shang +4AI Agents for Scientific Discovery Agentic Workflows
Shanghai Artificial Intelligence Laboratory, Shanghai, China · Nanjing University, Nanjing, China
Boltzmann-Expected Molecular Design with Decoupled Annealing Flows
Jul 21, 2026Selma Moqvist, Richard Beckmann, Ross Irwin +2Molecular Optimization Molecular Graph Generation
Department of Computer Science and Engineering Chalmers University of Technology & University of Gothenburg SE-41296 Gothenburg, Sweden · Molecular AI Discovery Sciences, R&D AstraZeneca SE-43183 Mölndal, Sweden
DBMol: Design of High-Affinity, Target-Specific Small Molecules through Structure Prediction Models
Jul 21, 2026Yiming Qin, Kai Yi, Miruna Cretu +3Protein-Ligand Binding Affinity Prediction Molecular Optimization
EPFL, Switzerland · MRC-LMB, UK · University of Cambridge, UK
HEDGEHOG: Hierarchical Evaluation of Drug Generators Through Rigorous Filtration
Jul 14, 2026Daria A. Ryabchenko, Pavel Gurevich, Shamil Kadyrov +5Molecular Generation Generative AI Evaluation
Ligand Pro, Moscow, Russia · Skolkovo Institute of Science and Technology, Artificial Intelligence Center, Moscow, Russia · 1Ligand Pro, Moscow, Russia +1
Generating Developable 3D Molecules via Pocket-Conditioned Diffusion and Property-Aware Optimization
Jul 14, 2026Ruoxi Gao, Jiangweizhi Peng, Ziqi Chen +10Molecular Optimization Structure-Based Drug Design
Computer Science and Engineering, The Ohio State University, Columbus, OH 43210. · Industrial and System Engineering, University of Minnesota, Minneapolis, MN 55455. · Google Cloud, Google LLC, Mountain View, CA 94043. +6
Gene Expression-Informed Jointly Controlled Generative Modeling for Precision Molecular Design
Jul 13, 2026Hang Yuan, Chen Li, Wenjun Ma +2Molecular Optimization Molecular Generation
School of Artificial Intelligence South China Normal University Foshan, Guangdong, China · D3 Center The University of Osaka Suita, Osaka, Japan · School of Computer Science South China Normal University Guangzhou, Guangdong, China
BFMT: Enhancing Search Capabilities of Tree Sampler via Bootstrap Flow-Map Tree
Jul 3, 2026Binglin Ji, Anindya Sarkar, Hengchang Lu +4Inference-Time Search Image Generation
Department of CSE, Washington University in St.Louis, USA · Department of Information Technology, Uppsala University, Sweden
SynLaD: Latent Diffusion for Generating Synthesizable Molecules Conditioned on 3D Pharmacophore Profiles
Jul 1, 2026Miruna Cretu, John Bradshaw, Patricia Suriana +6Latent Diffusion Models 3D Molecular Generation
University of Cambridge, Cambridge, UK · Prescient Design (AI for Drug Discovery), Genentech, South San Francisco, USA · Work done during an internship at Prescient Design
Sesame: Structure-Aware Molecular Generation via Spatial Density-Map Conditioning
Jun 22, 2026Konstantin Yatsenko, Arvind ThiagarajanMolecular Generation Structure-Based Drug Design
Tessel Biosciences, Inc., 750 Main Street, Cambridge, MA 02139
JEDEL: Zero-Shot DNA-Encoded Library Design for Early-Stage Drug Discovery
Jun 21, 2026Zygimantas Jocys, Zhanxing Zhu, Henriette M. G. Willems +1Molecular Generation Drug Discovery
School of Electronics and Computer Science, University of Southampton, Southampton, SO17 1BJ, United Kingdom. · The ALBORADA Drug Discovery Institute, University of Cambridge,2026 Hills Road, Cambridge, CB2 0AH, United Kingdom.
My Chemical Harness: Evolutionary Molecular Design over Synthetic Pathways with Large Language Model Agents
Jun 8, 2026César Ojeda, Darius A. Faroughy, Maryam Karimi +3Molecular Optimization LLM Agents
Institute of Mathematics, Faculty of Science, University of Potsdam, Campus Golm, Building 9, Karl-Liebknecht-Str. 24–25, 14476 Potsdam-Golm, Germany · NHETC, Department of Physics and Astronomy, Rutgers University, Piscataway, NJ 08854, USA · Potsdam Transfer, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476 Potsdam. +1
Closing the Prior-Posterior Loop: Self-Reflective Molecular Design with Analysis-Driven LLM Iteration
Jun 8, 2026Junyi Gong, Zijie Qiu, Ben Zhong TangMolecular Optimization LLM Self-Refinement
Faculty of Chemistry, Shenzhen MSU-BIT University · School of Science and Engineering, Chinese University of Hong Kong (Shenzhen) · Department of Chemistry, Hong Kong University of Science and Technology
MolLingo: Molecule-Native Representations for LLM-Powered Scientific Agents
May 27, 2026Thao Nguyen, Heng JiMolecular Optimization Multi-Agent LLM Systems
Siebel School of Computing and Data Science, University of Illinois Urbana-Champaign

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MolHop: Scaffold-Hopping Molecular Design with Agentic Reinforcement Learning

Yanyi Su, Chenyan Wang, Yulei Gong, Yeyun Chen+2

State Key Laboratory of Physical Chemistry of Solid Surface, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, China · Shanghai Artificial Intelligence Laboratory, Shanghai, China · Institute of Artificial Intelligence, Xiamen University, Xiamen, China+1

Molecule Design Molecular Generation Drug Discovery RL for LLM Agents

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Molecular design is often formulated as an optimization problem over existing molecular spaces. However, molecular optimization and the discovery of structurally distinct replacement molecules represent two fundamentally different search problems. LLM-based molecular design agents typically perform the former, conducting local refinement within the neighborhood of existing structures to improve target properties through structural modifications. In contrast, the latter requires exploration of a broader chemical space to discover molecules with entirely different scaffolds while preserving the functional characteristics of reference molecules. We propose MolHop, an agentic framework for cross-scaffold molecular discovery that enables models to navigate and edit within a pre-organized chemical space. MolHop organizes approximately 1.6 million molecular scaffolds from commercial molecules into a coarse-to-fine hierarchical action space. The agent selects new exploration regions through scaffold navigation actions and adjusts candidate properties through molecular editing. The framework maintains historical trajectory memory to support long-horizon search processes. On drug molecule and commercial compound tasks, connecting Grok-4.6 and DeepSeek-Flash-V4.1 to the MolHop framework substantially improves their cross-scaffold joint success rates. We develop MolHop-9B through agentic reinforcement learning, and MolHop-9B outperforms generative baselines including GPT-5.6-sol, Claude-5-Opus, and Gemini-3.1-Pro, while generating candidate molecules with larger scaffold differences from the reference molecules. These results demonstrate that effective molecular discovery beyond the traditional optimization paradigm requires structured chemical and action spaces, enabling agents to explore new structural regions rather than merely refine existing molecules.